Procs
Claim this toolA modern, Rust-based replacement for the 'ps' command with enhanced features and readability.
Visit WebsiteFreeVisit Website
Tracked since2026
0 reviews trackedThe Bottom Line
Entry price
Free, no paid tier
Biggest pro
More informative and visually appealing than 'ps'
Biggest con
Requires sudo for full information access on other users' processes
TL;DR - Procs
- Modern 'ps' replacement written in Rust.
- Provides enhanced, human-readable process information.
- Supports multi-column search, watch mode, and tree view.
Pricing: Free forever
Best for: Individuals & startups
What is Procs?
Procs is a command-line utility written in Rust that serves as a modern and feature-rich alternative to the traditional 'ps' command for process management. It provides a more user-friendly and informative output, making it easier for developers and system administrators to monitor and understand running processes on their systems.
Key enhancements include colored and human-readable output, automatic theme detection, multi-column keyword search, and additional process information not typically available with 'ps', such as TCP/UDP port usage, read/write throughput, Docker container names, and more detailed memory information. Procs also offers pager support for long outputs, a watch mode similar to 'top', and a tree view for process hierarchies. It supports various platforms including Linux, macOS, and Windows, with experimental support for FreeBSD.
Available on: Linux, macOS, Windows
Pros & Cons
Pros
- More informative and visually appealing than 'ps'
- Cross-platform compatibility (Linux, macOS, Windows, FreeBSD)
- Easy installation via various package managers
- Provides additional insights like network and I/O usage
- Open-source and actively maintained
Cons
- Requires sudo for full information access on other users' processes
- Docker Toolbox on macOS not supported for container name display
- macOS support is experimental and primarily tested on GitHub Actions
Key Features
Colored and human-readable outputAutomatic theme detection based on terminal backgroundMulti-column keyword searchDisplay of TCP/UDP port informationDisplay of Read/Write throughputDisplay of Docker container namesMore detailed memory informationPager support for long outputs
Pricing Plans
Pricing checked Jul 15, 2026
Open Source
Free
- Full source code access
- MIT License license
- Community support
- Self-hosted
Reviews
$99Free with your review
Write a reviewReview Procs, get a free AI guide
Share your experience and we will send you Improve Your Thinking Patterns Using ChatGPT, free.
Explore More
Procs FAQ
How does Procs enhance process monitoring compared to traditional tools?
Procs provides a more user-friendly and informative output than traditional tools, including colored and human-readable text, automatic theme detection, and multi-column keyword search. It also offers additional process information such as TCP/UDP port usage and read/write throughput.
What kind of user would benefit most from using Procs?
Developers and system administrators would benefit most from Procs, as it simplifies monitoring and understanding running processes on their systems. Its enhanced features make it easier to gain insights into system activity.
Can Procs display information about Docker containers?
Yes, Procs can display Docker container names, providing more context for running processes. However, Docker Toolbox on macOS is not supported for this feature.
What are the limitations of Procs regarding process information access?
Procs requires 'sudo' privileges to access full information about processes owned by other users. Additionally, its macOS support is experimental and primarily tested on GitHub Actions.
How is Procs priced?
Procs is free to use, with no paid plans or subscriptions required. It is an open-source utility available for anyone to utilize.
Does Procs offer any features for continuous process observation?
Yes, Procs includes a watch mode, similar to 'top', for continuous process observation. It also provides pager support for navigating through long outputs and a tree view for visualizing process hierarchies.
Source: github.com